Consider the set of features of positive regions-of-interest (ROIs) \(R_{feat} = \lbrace f_{i}\rbrace _{i\in N_{roi^+}}\)  consisting of feature vectors generated by the object detector \(\phi _s\)  of ROIs categorized as belonging to the object class. In order to create a representative prototype, we take inspiration from [1]} and send the ROI features as tokens to a transformer module consisting of a linear embedding layer and a set of transformer encoders. The encoder contains alternating multi-head attention blocks and feed-forward blocks, with interspersed normalization layers and residual connections, as depicted in Figure REF .
